Therapeutic research works using BDNF.
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",isbn:"978-1-83969-057-0",printIsbn:"978-1-83969-056-3",pdfIsbn:"978-1-83969-058-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"5f388543a066b617d2c52bd4c027c272",bookSignature:"Prof. Christophe Hano and Dr. Jen-Tsung Chen",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10539.jpg",keywords:"Plant Description, Botany, Phylogeny, Genome, Phytochemical Analysis, Extraction, Phytochemical Diversity, Phytochemical Analysis, Extraction, Phytochemical Diversity, Biotechnological Production, Traditional Medicinal Uses",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 8th 2020",dateEndSecondStepPublish:"November 23rd 2020",dateEndThirdStepPublish:"January 22nd 2021",dateEndFourthStepPublish:"April 12th 2021",dateEndFifthStepPublish:"June 11th 2021",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Assistant Professor at the University of Orleans at Research INRAE Lab LBLGC USC1328 and a member of the Cosm'ACTIFS Research Group (CNRS GDR3711). He authored and co-authored more than 100 scientific papers, reviews, and book chapters in internationally renowned journals.",coeditorOneBiosketch:"Dr. Jen-Tsung Chen is currently a professor at the National University of Kaohsiung in Taiwan. He teaches cell biology, genomics, proteomics, medicinal plant biotechnology, and plant tissue culture in college. Dr. Chen's research interests are bioactive compounds, chromatography techniques, in vitro culture, medicinal plants, phytochemicals, and plant biotechnology. He has published over 60 research papers, reviewed over 260 manuscripts, and edited at least 150 papers in international peer-review journals.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"313856",title:"Prof.",name:"Christophe",middleName:null,surname:"Hano",slug:"christophe-hano",fullName:"Christophe Hano",profilePictureURL:"https://mts.intechopen.com/storage/users/313856/images/system/313856.jpg",biography:"Dr. Christophe Hano (male, 1978), who completed his PhD in 2005 in Plant Physiology, Biochemistry and Molecular Biology, is now Assistant Professor at the University of Orleans at Research INRAE Lab LBLGC USC1328 and a member of the Cosm'ACTIFS Research Group (CNRS GDR3711). His research career has focused on applied plant metabolism and plant biotechnology. He has written more than 100 scientific papers, reviews and book chapters in internationally renowned journals and edited one book as well as a variety of journal topical issues on plant secondary metabolism, including polyphenols. He is Academic, Assistant Editor and/or Editorial Board Member of several renowned Q1 Journals in Plant Biochemistry and Biotechnology (including Plos ONE, Biomolecules, Plant Cell Tissue and Organ Culture, Frontiers in Plant Science, Cosmetics). He was reviewers for more than 500 papers for ca 35 International Journals, and recognized scientific expert for several national and international Institutions. Currently, he is developing research projects aimed at studying plant secondary metabolism to lead to the development of natural products with interests in pharmacology or cosmetics. His research focuses on the green extraction and analytical methods applied to plant polyphenols, elucidation of biosynthetic mechanisms of plant natural products and their exploitation by metabolic engineering approaches. He was a leader (project manager) in 6 scientific projects and major investigator in several more. In this context he conducts research projects in cooperation with industrial companies and he coordinates in the European Le Studium® Consortium Action on the bioproduction of bioactive extracts for cosmetic applications through plant cell in vitro cultures. In this context, he explores the potential of the Loire Valley Flora Area for cosmetic applications. (Cited over 1450 times; H=20; i10=44; orcid.org/0000-0001-9938-0151).",institutionString:"Laboratoire de Biologie des Ligneux et des Grandes Cultures INRA USC1328",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Orléans",institutionURL:null,country:{name:"France"}}}],coeditorOne:{id:"332229",title:"Dr.",name:"Jen-Tsung",middleName:null,surname:"Chen",slug:"jen-tsung-chen",fullName:"Jen-Tsung Chen",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000031RJmlQAG/Profile_Picture_1600760167494",biography:"Dr. Jen-Tsung Chen is currently a professor at the National University of Kaohsiung in Taiwan. He teaches cell biology, genomics, proteomics, medicinal plant biotechnology, and plant tissue culture in college. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"40609",title:"Non-Linear Energy Harvesting with Random Noise and Multiple Harmonics",doi:"10.5772/50727",slug:"non-linear-energy-harvesting-with-random-noise-and-multiple-harmonics",body:'Harvesting energy from background mechanical vibrations in the environment has been proposed as a possible method to provide power in situations where battery usage is impractical or inconvenient. The most commonly used method for energy harvesting is to generate power from the vibrations of a piezoelectric material [1-3]; other methods include electromagnetic inductive coupling [4-6] and charge pumping across vibrating capacitive plates [7-10]. It has been shown that a piezoelectric cantilever attached to a vibrating structure can be used to power wireless transmission nodes for sensing applications [9]. In order to generate sufficient power, the frequency of the vibration source must match the resonant frequency of the piezoelectric cantilever. If the source vibrates at a fixed, known frequency, the dimensions of the cantilever, and the proof mass can be adjusted to ensure frequency matching. Many naturally occurring vibration sources do not have a fixed frequency spectrum, however, and vibrate over a broad range of frequencies. Lack of coupling of the piezoelectric cantilever to the off-resonance vibrations means that only a small amount of the available power can be harvested.
Recent reports have shown that the resonant frequency of a simply supported beam [11] or a piezoelectric cantilever [12] can be tuned by applying an axial force. Research also show that the resonant frequency of a cantilever can also be manipulated by applying a transverse force on the cantilever [13,14]. (In all these cases, the cantilevers response remained within the linear regime.) In principle, this effect could be developed into an active tuning scheme which matches the cantilever resonance to the maximum vibrational output of the environment at any particular time. Calculations indicate, however, that the power consumed by active tuning completely offsets any improvement obtained in the scavenging efficiency [15]. More promising are passive tuning schemes in which a fixed force modifies the frequency response of the cantilever beam, without requiring additional power input. For example, an attractive magnetic force acting above the cantilever beam reduces the spring constant of the cantilever and lowers the resonance frequency [13,14], while an attractive force acting along the axis of the cantilever applies axial tension, and increases the resonance frequency [12]. While this can be used to tune the resonant frequency, there is no increase in output power, and the cantilever motion can even be dampened by the magnetic force and the resulting power output reduced [12,13].
The use of a magnetic force to introduce non-linear oscillation in cantilever motion has recently been reported [16-18]. A pendulum made with piezoelectric material [16] was used to study the energy output under different strengths of random Gaussian noise. An improvement of between 400% and 600% was observed compared to a standard linear oscillator. A piezomagnetoelastic structure [17] with two external magnets was studied, in which chaotic motion was observed outside the resonance frequency. It was further reported [18] that the softening response of a cantilever due to a magnetic attractor expands the response bandwidth and also increases the off resonant amplitude significantly.
Stochastic motions have been long observed with a pendulum in a repulsive magnetic field [19-20] In a generalization effort, the optimal relationship among the physical parameters for a coupling enhancement was provided in [16] [Cottone et al., 2009] using Duffing oscillator. Improvements for the non-linear system have been attributed to an advantage in the amplification of the vibration response from energy harvesters in the stochastic regime [17-18].
Here, we will first demonstrate how this capability can be used to improve power output from a broadband vibration source, having a 1/f frequency dependence (pink noise) [21]. Note that a 1/f vibration spectrum describes a vibration source in which the power spectral density of the vibration is inversely proportional to frequency. Since many naturally occurring vibration sources display a 1/f dependence, this provides evidence that the magnetic coupling could be used for more efficient energy harvesting in practical settings.
The second part of this chapter provides an in-depth study of the response of a magnetically coupled cantilever at different frequencies [22-23]. It is our observation that amplification of the cantilever output occurs not only under stochastic motion but also due to subharmonic and ultraharmonic resonance in the vicinity of the main resonant frequency. The partial solutions of subharmonic and ultraharmonic are intrinsically embedded in the magnetic coupled equation as derived in forced oscillations of weakly nonlinear systems [24]. For a particular weakly coupled cantilever experimented in this paper, maximum output is maintained at the resonant frequency through combination of ultra-harmonic components. In a singly parametric excited scan of voltage production with non-linear piezoelectric cantilever, four distinct types of efficiency improvements are observed, in which the signal is amplified above the linear cantilever operation: (1) ultraharmonic amplification below resonance; (2) stochastic amplifications in multi-frequency and multi-amplitude oscillations; (3) ultra-sub-harmonic amplification at multiple quarter frequencies; (4) sub-harmonic amplification at one-third frequencies. For data analysis, a 1-D non-linear system coupled with piezoelectric charge production is modeled to illustrate the dynamic functions.
Figure 1 shows the set-up for the magnetically coupled piezoelectric cantilever measurements. The cantilever is manufactured using commercially available unimorph piezoelectric discs composed of a 0.9 mm thick PZT layer deposited on a 1 mm thick brass shim (APC International, MFT-50T-1.9A1). The disc is cut into a 13 mm wide by 50 mm long strip, and clamped at one end to produce a 44 mm long cantilever. The PZT layer extends 25 mm along the length of the cantilever, and the remainder is brass only. The proof mass (including the magnet and an additional fixture that holds the magnet) weighs 2.4 gm, while the cantilever itself weighs 0.8 gm. The electrical leads are carefully soldered with thin lead wires (134 AWP, Vishay) to the top side of the PZT and the bottom side of the shim [21].
The experimental set-up for the magnetically coupled (non-linear) piezoelectric cantilever. The magnetic force is repulsive and bi-directional.
Vibration is generated by a shaker table (Labwork ET-126) driven by an amplified pink noise source (Labwork Pa-13 amplifier). The pink noise is generated numerically, with amplitude and crest factor set to -4dB and 1.41, respectively. The average shaker table acceleration is 7.5 m/s2, independent of the magnetic coupling. A custom Labview data acquisition program measures output voltage from the cantilever beam and the acceleration from the shaker table, once every second. The voltage peak to peak (Vpp) is measured by an oscilloscope (Agilent 54624A), and the dc voltage is detected with a digital multi-meter (YOGOGAWA 7561). A 5mm diameter round rare earth magnet (Radio Shack model 64-1895) is attached to the vibrating tip of the cantilever beam, while a similar opposing magnet is attached directly to the shaker table frame, with repulsive force. The distance between the magnets is adjusted to 5.5 mm, to make the magnetic force comparable to the spring force of the cantilever.
The voltage generated by the cantilever in response to the pink noise source is measured using three different circuits, (shown in Figures 2(a), 3(a), and 4(a)). In each case, the output from the coupled cantilever is compared with the output from the same cantilever in the uncoupled situation (with the opposing magnet removed). In Figure 2, the piezoelectric cantilever beam is wired directly to an oscilloscope with a 1 M Ohm input impedance and the peak-to-peak output voltage, Vpp is measured. As shown in Figure 2 (b) the cantilever output is seen to fluctuate as a function of time, reflecting the random nature of the vibrations. For much of the time, the output from the coupled and uncoupled cantilevers is similar. However, occasionally, very large voltage spikes are observed in the output from the coupled cantilever, that are not observed for the uncoupled case. The voltage peak to peak spans to 5.7 V (min. 0.7 V and max. 6.4 V) with the coupled setup and only 2.2 V (min. 0.9 V to max. 3 V) volts with the uncoupled cantilever. The overall RMS powers for the uncoupled cantilever are 3.95 µW and 4.85 µW for the coupled case. The ratio of the maximal voltage output from the coupled to the uncoupled is 2.1.
In Figure 3, the voltage generated by the piezoelectric cantilever beam is rectified, using 0.4 V forward biased diodes, and detected across a 22 µF capacitor and a 1 M Ohm resistor in parallel. As shown in Figure 3(b), the amplitude of the voltage output with this measurement circuit is most of the time higher in the coupled case than in the uncoupled case. This is because the RC decay time of the circuit is larger than the time between the large amplitude deflections of the cantilever. The average voltage measured across the capacitor or the voltage integration over time is approximately 50% higher in the coupled case.
a) The open circuit measurement on Vpp directly from the piezoelectric cantilever, and (b) the higher swing voltage reflects the voltage generated by coupling setup with larger cantilever motions.
a) The schematic of a rectified circuit with a 1 M Ohm resister, and (b) the fluctuations of the voltage indicate that more power being generated by the magnetic coupled cantilever.
In Figure 4, the rectified voltage is measured directly across the 22 µF capacitor without the 1 M Ohm resistor. As shown in Fig. 4(b), the voltage across the capacitor increases with time, until a maximum charging voltage is achieved. The maximum voltage measured across the capacitor is approximately 50% higher in the coupled case than in the uncoupled case. Note that there is a time delay for the coupled cantilever to achieve a higher voltage than the uncoupled cantilever. This is due to the time passing before the first large amplitude deflection occurs. The random nature of the motion means that this time will vary from run to run, however, on average the coupled cantilever output will be consistently higher than the uncoupled output. Note that in addition to producing more power, the higher voltage output enables circuit operation without a step-up transformer, eliminating the power loss in the transformer.
a) The schematic of the storage circuit, and (b) DC voltage output measured on the storage capacitor indicating more charge is stored with the magnetic coupling setup.
It is instructive to compare the force exerted on the cantilever in the coupled and uncoupled cases. To do this, an empirical measure of the magnetic force is obtained using the experimental set-up shown in Figure 5.
The magnetic force component function, Fz, is determined by the electronic scale versus the manual deflection of the cantilever.
The opposing magnet is mounted onto a measurement scale, and the position of the magnetized cantilever is manipulated by pushing up and down at the end of a cantilever beam, simulating flexure movement. The deflection z is measured using a micrometer, while the reading on the scale provides the force between the two magnets. The details of the force measurments were shown in [22]. Only the magnetic force in the z direction, Fz, contributes to the resultant spring force. At z=0, the force is zero in the z direction because the two magnetic forces only repel each other in the longitudinal direction. Fz increases as the angles between the two magnets increase until the overlap between the two magnets is zero. At this point, Fz decreases with increasing distance because the force is inversely proportional to the distance squared.
The spring force, the magnetic force and the resultant force (spring plus magnetic) are plotted in Figure 6,
The plot shows the magnitude of the magnetic forces exerted on the cantilever beam, the spring forces and the resultant forces.
The resultant force is significantly reduced compared to the bare spring force near z=0. The coupled system has three equilibrium points where the resultant force is zero, compared to the single equilibrium point of the bare spring force. Because the resultant force in the region of the three equilibrium points is relatively small, transitions between the three points occurs relatively easily. Note that the middle equilibrium is unstable, therefore when the piezoelectric cantilever is set up for the coupling experiment, the cantilever is off the equilibrium point toward ground in static state as shown in Figure 1. In Figure 7 the potential energy is plotted for both the uncoupled and coupled systems. The potential energy is calculated by direct integration of the force with respect to the displacement, z. This gives for the uncoupled case, and for the coupled case. For the coupled case, the resultant potential is raised, with two local minima symmetric to z=0. This double well structure allows easy movement of the cantilever beam even when excited by non resonant forces. Once it passes the local high potential, it drifts to the other side of the balance, resulting in an increased total deflection distance. This can be seen by considering the possible motion of the cantilever beam having a kinetic energy, h, which is large enough to surmount the potential barrier at z=0. With the same random acceleration background the coupled cantilever can travel further distance than the uncoupled one. The voltage output, which depends on the movement of the cantilever, therefore, increases. The ratio of the maximum displacement in the coupled and uncoupled systems determined from Figure 7 is 2.4. This is comparable to the ratio of maximum voltage output in the coupled and uncoupled systems, which was seen in Figure 2 (b), at 2.1.
The direct integration from the measured forces function in Fig. 6 leads to the magnetic potential, spring potential and the resultant spring potential. The responding range in the coupled and the uncoupled cantilever is defined by the same potential height, h.
The magnetic coupling (although a passive force requiring no energy) introduces a symmetric force which acts in the opposite direction to the spring force around z=0. Being comparable in magnitude to the spring force, the magnetic force compensates the spring potential, and introduces a double valley in the potential energy profile. Under the influence of the modified spring potential, the magnetically coupled cantilever responds to a random vibration source (like the pink noise) by moving chaotically between the two minima in the potential energy profile. As compared with the non-chaotic motion of the uncoupled cantilever around the single z=0 potential minimum, this produces larger cantilever deflection and more voltage output from the piezoelectric cantilever. The oscillations around the resonance frequency are unstable and chaotic, but persistent. The modified spring potential is higher, and flatter than the bare spring potential, making the magnetic coupled cantilever easier to excite in the random frequency region. The experiments show that the ratio of the open circuit peak to peak voltage output and the potential well are closely related. Future work includes the design and implementation of modified potential wells and further analysis of the gain due to the modified potential wells.
The experiment set up is the same as Figure 1. In all measurements, the shaker table acceleration is set to approximately 4.2 m/s2 at resonant freqeuncy, and the frequency swept from 0 to 30 Hz in 0.5 Hz steps. The opposing magnet fitted at the free end of the cantilever supplies a symmetrical, repulsive force about the balance of the cantilever during vibration. The horizontal separation between the magnets (designated by ) is adjusted to be approximately between 6 to 6.5 mm. This separation is found to provide the best compensation for the spring force, and makes the effective restoring force as small as possible near the equilibrium point.
Figure 8 shows both the output of the piezoelectric cantilever as a function of shaker table vibration frequency for the linear and non-linear case. The voltage generated by the piezoelectric cantilever beam is directed measured by oscilloscope treated as an open circuit. At the resonance frequency (measured to be 9.5 Hz) the output of the cantilever was 53 V, and the peak height, resonance frequency and line width are all approximately the same for the linear and non-linear states (here linear refers to the non-coupled state, while non-linear refers to the magnetically coupled state). On either side of the main resonance, however, there is additional output observed for the non-linear cantilever, which is not observed in the linear state. As can be seen from a comparison of the linear and the non-linear runs, the overall amplitude profile of the non-linear run is much larger in the sense of a broadband distribution, although there are gaps between peaks in the overall pattern of the non-linear output.
Figure 9 shows the output of both the linear and non-liner cantilever measured as a function of time at selected frequency to illustrate the comparison of the linear and non-linear dynamics. The voltage output of the non-linear cantilever evolves with frequency, while being amplified close to the resonance frequency. The spectrum shows a variety of amplified motions and harmonics. For example, at a driving frequency as low as 6.5 Hz (between 6-7.5Hz) (Figure 9(a)) both the linear and non-linear cantilever motions follow the vibrations of the shaker table, producing periodic oscillations. The amplitude of the oscillations for the non-linear cantilever is 5 times larger than those for the linear cantilever, however. At the resonant frequency (Figure 9(b)) both linear and non-linear cantilevers oscillate at the driving frequency with equal amplitudes. At 13 Hz (Figure 9(c)) the linear cantilever motion continues to follow the vibrations of the shaker table, producing low amplitude periodic oscillations. The non-linear cantilever motion is aperiodic and has a magnitude which is on average 3 times larger than that of the linear cantilever. At 16 Hz (Figure 9 (d)) the non-linear cantilever produces a 3 times larger peak to peak amplitude than the linear cantilever, and shows multiple and periodic “half-way” vibrations. At 20Hz (Figure 9 (e)) the non-linear cantilever shows a 5 times larger amplitude at the frequency of 6.7Hz than the linear output at 20 Hz.
The voltage output (peak to peak) of the piezoelectric cantilever measured as a function of frequency (dash line for linear and solid line for non-linear state).
Note should be taken that there are two unexpected small peaks at 12.5 Hz and 17 Hz for the linear response. The peaks at 12.5 Hz and 17 Hz on the experiment data come from the torsion and standing wave oscillations. It is the result of how the piezoelectric cantilever was facilitated with magnet and its fixture as the proof mass. The cantilever is relatively thin and droops naturally due the weight of proof mass a few millimeters (as shown in Figure 1) to a curve. The L-shape fixture that holds the magnet was bolted with a screw on one side parallel to the brass shim. The magnet is then attached on the other side of the L-shape fixture, perpendicular to the brass shim in such way to make magnetic coupling. During the process, the cantilever was deformed and twisted slightly. As a result, the combined proof mass is slightly located off the center of the cantilever beam resulting in weight imbalance and torsion mode resonance. The fixture also creates an area where the free end is rigid with the fixture, which acts like a semi-fixed end, paving a way for a standing wave vibration when the cantilever is excited. Finite Element Analysis (FEA) simulating the structure and dimensions confirms that the first 3 modes of vibration include bending, torsion and standing wave oscillations.
The output of the linear (dash line) and non-linear (solid) system in the time domain: (a) 6.5 Hz (b) 9.5Hz at resonance; (c) 13 Hz ; (d) 16Hz ;(e) 20Hz
The dynamics of the piezoelectric cantilever is modeled by a 1-D driven spring-mass system coupled with the piezoelectric effect under the influence of a magnetic force Fm(z) [17-18]:
with mass m=0.0024 kg, damping coefficient d=0.0075 kg/sec, spring constant k=8.55 N/m, and angular frequency ω. Here, z is the vertical deflection of the cantilever, V is the generated voltage, σ=5x10-6 N/V is the coupling coefficient, and A is the acceleration of the shaker table (A=4.2 m/sec2 measured at resonance frequency). The voltage output is related to the deflection of the piezoelectric cantilever through:
where Rl is the equivalent resistance, Cl is the equivalent capacitance and 1/ (Rl Cl)= 0.01, and θ=1250 is the piezoelectric coupling coefficient in the measured circuit. The transverse magnetic force (in the z direction) is determined from the force between two magnetic dipoles (Kraftmakher, 2007):
where M is the dipole magnetization, u0 is the permeability in air, and η is the horizontal separation between the magnets at z=0. The correction factors a and b are included to compensate for the flexure motion of cantilever and the magnetic force along the cantilever axis [16]. The magnetization M is determined by direct measurement of the axial force between the cantilever and a fixed magnet using a reference scale [22].
The solution to the coupled differential equations (1) and (2) is determined using Maple software to give the voltage output versus time for a given driving frequency, magnetic force function, and separation η. In order to fit our experiment data, the magnetic force Fm(z) was modified by a and b parameters and used for our calculation, where M = 0.011Am2, η = 6.5 mm, a = 1.04 and b = 1.21. As in the experiment, the output is calculated for t = 0 to 10 seconds, and the maximum peak-to-peak output over the last 2 seconds obtained. The result of the frequency domain is showed in Figure 10, which resembles the experimental result as seen in Figure 8.
Both the experiment and simulation figures show broadband vibration for the non-linear configuration between 6-20Hz. The simulation in Figures 11(a)-(e) reproduces many of the features observed in the experiment in Figures 9(a)-(e). The rest of Figures 11-15 reveals more about the complexity of the multiple harmonics in the non-linear systems. The simulations of the time domain with the corresponding frequency selected from experiment are shown in Figures 11(a)-15(a). Figures 11(b)-15(b) illustrate the velocity vs. voltage output of the piezoelectric cantilever in both the linear and non-linear cases. Figures 11(c)-15(c) are the Fourier transform of the coupled cantilever cases in Figures 11(a)-15(a), respectively, showing the compositions of frequency components for the non-linear states. The following section will discuss the multiple harmonic components directly derived from the non-linear dynamics simulations.
The simulated voltage output (peak to peak) of the piezoelectric cantilever is plotted in the frequency domain (dash line for linear and solid line non-linear).
At a driving frequency of 6.5 Hz, as seen in Figure 11(a), both the linear and non-linear cantilever motion follow the vibrations of the shaker table, producing periodic oscillations. The amplitude of the oscillations for the coupled cantilever, however, is approximately 5 times larger than those for the linear cantilever, as seen in the experiment in Figure 9(a). The velocity vs. voltage in Figure 11(b) shows that the coupled cantilever has non-linear component in voltage production. Further analysis through Fourier transformation indicates that the non-linear cantilever shows the combination of the excited 6.5 Hz harmonic (dominant and high amplitude) and the 20 Hz ultraharmonic (3 times the excited frequency), as seen in Figure 11(c).
At the resonant frequency of 9.5 Hz (Figure 12(a)) both non-linear and linear cantilevers oscillate at the driving frequency with equal amplitude of voltage output. The responses for both the coupled and uncoupled cantilever at resonant frequency are almost identical in the voltage output. The velocity vs. voltage in Figure 12(b) shows a little non-linearity at 90o and -90o of the vibration cycles. Through Fourier transformation as seen in Figure 12(c), the non-linear cantilever shows some components of vibration at the excited 9.5 Hz harmonic (dominant) and the 29 Hz ultraharmonic (3 times the excited frequency).
The theoretical analysis of excited frequency at 6.5 Hz. (a) the time domain voltage output, dash line for linear and solid line for non-linear states; (b) the velocity vs. voltage output, dark line for linear and light line for non-linear state; (c) the Fourier transform of the non-linear state from the data of Figure 5(a).
The theoretical analysis of excited frequency at 9.5 Hz. (a) the time domain voltage output, dash line for linear and solid line for non-linear state; (b) the velocity vs. voltage output, light line for linear and dark line for non-linear state; (c) the Fourier transform of the non-linear state from the data of Figure 12(a).
The response for the non-linear cantilever is chaotic at 13 Hz as seen in Figure 13(a), but with average 3 folds larger magnitude than the linear one. The velocity vs. voltage relation in Figure 13(b) shows chaotic motions for the coupled cantilever. Using Fourier transformation for Figure 13(a) results in Figure 13(c), the coupled cantilever shows the linear response of a small portion of 13 Hz component combined with a large amplitude distribution at lower frequency that are attributed to the chaotic motion. Note that the small peaks at 12.5 Hz and 17 Hz are not observed in the simulation as seen and discussed in the experiment section. This small torsion and standing wave bending resonance are not accounted for by the simplified 1-D model used to simulate the spring mass damping model such as an ideal cantilever.
At 16Hz, the non-linear cantilever is periodic (Figure 14(a)) and is 3 times larger (peak to peak) in magnitude than the uncoupled one, with double prone of low frequency in the upper cycle. Apparently, it is and composed of different frequency and multiple haromonic motion, with large magnitude than the uncoupled motion. The evidence is also shown in the velocity vs. voltage relationship in Figure 14(b), where 3 different cyclic loops are identifiable. Fourier transformation from time data in Figure 14(a) proves that the non-linear cantilever delivers ultra-sub-harmonic vibration at n*(16/4) Hz, where, n=integer in Figure 14(c).
The theoretical analysis of excited frequency at 13 Hz. (a) the time domain voltage output, dash line for linear and solid line for non-linear states; (b) the velocity vs. voltage output, light line for linear and dark line for non-linear state; (c) the Fourier transform of the non-linear state from the data of Figure 13(a).
The theoretical analysis of excited frequency at 16 Hz. (a) the time domain voltage output, dash line for linear and solid line for non-linear states; (b) the velocity vs. voltage output, light line for linear and dark line for non-linear state; (c) the Fourier transform of the non-linear state from the data of Figure 14(a).
At 20Hz, the response for the non-linear cantilever is periodic and also 3 folds larger peak to peak magnitude than the linear one as seen in Figure 15 (a). The velocity vs. voltage in Figure 15(b) shows some combination of cyclic motions for the non-linear cantilever. Through Fourier transformation, the coupled cantilever shows subharmonic at 6.7 Hz (dominant), excite frequency/3, and 20 Hz in Figure 15(c).
The combination of the stochastic and various harmonic features have three to five folds greater voltage production than the linear standard narrow band piezoelectric cantilever. Together with the un-damped resonant response enhance the performance well beyond that of a standard energy harvester.
The theoretical analysis of excited frequency at 20 Hz. (a) the time domain voltage output, dash line for linear and solid line for non-linear states; (b) the velocity vs. voltage output, light line for linear and dark line for non-linear state; (c) the Fourier transform of the non-linear state from the data of Figure 15(a).
Figure 16 (a) shows the output of the other PZT cantilever with similar specs as a function of shaker table vibration frequency for the case where the opposing magnet is fixed to the shaker table. The voltage generated by the piezoelectric cantilever beam is rectified, and detected across a 22 µF capacitor and 1 M Ohm resistor in parallel, using the circuit shown in Figure 3 (a). The results from two measurement runs in the coupled state are shown, together with the output of the cantilever measured in the uncoupled state. (This is obtained by removing the opposing magnet.) At the resonance frequency, (measured to be approximately 10 Hz) the output of the cantilever exceeds 16 V, and the peak height, resonance frequency and linewidth are all approximately the same for the coupled and un-coupled states. On either side of the main resonance, however, there are additional output observed for the coupled cantilever, which is not observed in the uncoupled state. As can be seen from a comparison of the two coupled runs, the frequency distribution of the peaks are the result of the multiple harmonics, as predicted in the open circuit.
Voltage output of the piezoelectric cantilever as a function of shaker table frequency for (a) single cantilever (b) double cantilever. Integrated voltage output as a function of frequency for (c) single cantilever and (d) double cantilever.
Also measured was a double cantilever system, (as shown in Fig. 16(b)), in which the second magnet is connected to an opposing cantilever (having resonant frequency of around 60Hz) rather than to a fixed point. As shown in Fig. 16 (b), the results are similar to the single cantilever system, except that the double cantilever system shows a larger overall increase in off-resonance output. The overall improvement in the harvesting efficiency can be illustrated by plotting the integrated voltage output of the cantilever beam as a function of frequency. For both the single (Fig. 16 (c)) and double (Fig. 16 (d)) cantilever systems, the integrated voltage output over the 0-30 Hz bandwidth shows a substantial increase in the coupled versus the uncoupled case. The total improvement is 31%-87%, with some variation between measurement runs.
Piezoelectric cantilevers have been widely studied for energy scavenging applications, but suffer from poor output power outside of a narrow frequency range near the cantilever resonance. In this chapter, we have demonstrated how power output can be enhanced by applying a simple passive external force. When a symmetrical and repulsive magnetic force is applied to a piezoelectric cantilever beam to compensate the cantilever spring force, this lowers the spring potential and increases the output when driven by a random pink noise vibrational source. The principle may be applied to other vibration energy harvesting devices such as electromagnetic and capacitive types in random naturally pink noise environments.
In the parametrically excited piezoelectric cantilever experiments, linear and non-linear performances were compared. Overall, four distinct types of efficiency improvements appear in the non-linear configuration, in which the signal is amplified above the linear cantilever response: low frequency ultraharmonic amplification; stochastic amplifications in multi-frequency and multi-amplitude oscillations; ultra-sub-harmonic amplification at multiple quarter frequencies; subharmonic amplification at one-third frequencies. Taken together, the stochastic, sub-harmonic and ultra-harmonic response produces an average of three to five-fold increase in voltage production. For energy harvesting purposes, the combination of the four features together with the un-damped resonant response enhances the performance well beyond that of a standard energy harvester. Furthermore, an analytical model of the bi-stable dynamics produces results consistent with those observed experimentally. The simulation tool could be deployed in the future investigation for non-linear energy harvester design for broadband and beyond natural harmonic applications.
The effort was funded by the Department Of Energy DE-FC26-06NT42795 and the U.S. Navy under Contract DAAB07-03-D-B010/TO-0198. Technical program oversight under the Navy contract was provided by Naval Surface Warfare Center, Crane Division.
Parkinson’s disease is the second most common neurodegenerative disease worldwide, with high annual costs of treatment. The death of dopaminergic neurons and inflammation are the main cellular processes associated with motor and cognitive dysfunctions in PD [1, 2, 3, 4]; these events can be potentiated by the loss of the brain-derived neurotrophic factor (BDNF), a key neurotropic factor in degeneration and regeneration processes.
BDNF, discovered in 1982, is a pleiotropic neurotrophin (NT). The gene encoding for BDNF is located on chromosome 11p14.1. Under normal conditions, this neurotrophic factor is synthesized as a non-covalently bound homodimer that contains a signal peptide next to the initiation codon, a pro-region containing an N-linked glycosylation site, and interacts with its receptor as a homodimer [5]. The BDNF gene, in rodents, consists of nine untranslated 5′ exons, each linked to individual promoter regions, and a 3′ coding exon (IX), which encodes the amino acid sequence of the BDNF pre-protein. Similarly, human BDNF gene also consists of multiple 5′ exons spliced to a single 3′ coding exon. The transcription of neurotrophins is finely regulated by several intracellular signaling pathways and by different transcription factors [6].
This NT is synthesized as an inactive precursor form, pre-pro-BDNF that can be cleaved to form a mature neurotrophin that is transported to the plasma membrane and then released in an unprocessed manner. The “pre” sequence is normally deleted when it translocates through the Golgi membrane, producing the pro-BDNF of 32 kDa. Small amounts of a truncated 28 kDa pro-BDNF can also be formed in the endoplasmic reticulum without interfering with the final levels of active, mature 14 kDa BDNF (m-BDNF). The N-terminal pro-domain of BDNF facilitates intracellular trafficking and regulated secretion. After cleavage of N-terminal region, the m-BDNF is released, although this does not exclude the release of the pro-BDNF form [6].
The BDNF shows affinity for two types of receptors. The first is a 75 kDa glycoprotein from the family of tumor necrosis factor receptors, represented by p75 NTR and P75 + sortilin receptors, and the second is a receptor from the protein tropomyosin receptor kinase (Trk) family, which involves the TrkA, TrkB and TrkC, whose main ligands are neuronal growth factor (NGF), BDNF/neurotrophins (NT-4 and NT-3), respectively. The p75 receptor binds to the pro-BDNF isoform and can induce apoptosis and bind non-neurotrophic ligands such as the glycoprotein of rabies virus, amyloid peptides and also other pro-neurotrophins; it can also generate neurite retraction and synaptic weakening and facilitate long-term depression [6, 7, 8]. The m-BDNF binds to TrkB receptors promoting cell survival, neurite extension and long-term synaptic potentiation and improves learning and memory; it also promotes synaptic plasticity, neurogenesis, formation of angiogenic tubes, regulation of neurotransmitter release and dendritic growth [5, 6, 9, 10, 11].
At the brain level, BDNF is produced in the hippocampus, amygdala, stria terminalis, septum, nuclei of the solitary tract and cortex [8, 12], where it regulates the survival and differentiation of various neuronal populations, including sensory neurons, cerebellar neurons and spinal motor neurons. However, it was observed that the brain is not the only source of BDNF, since its expression has been demonstrated in human immune cells (T or B cells and monocytes), adipose tissue cells, β-cells, vascular endothelial cells and in blood [13, 14]. Its presence in ovaries has also been described, where it participates in folliculogenesis [15]; in the heart [16] and in other organs, it participates in angiogenesis and immunomodulation process [17]. The presence of BDNF in other organs of the body raises the hypothesis that exogenous neurotrophic factors provide a symptomatic treatment during the patient’s disease state rather than a cure for the nervous system disorders that cause the disease [18].
Alterations of BDNF expression are implicated in the development of a variety of central nervous system (CNS) diseases, including neurodegenerative disorders, such as Alzheimer’s, Parkinson’s, Huntington’s disease and amyotrophic lateral sclerosis, and psychiatric disorders, such as depression and schizophrenia [14, 18]. However, several studies have shown that the therapeutic application of BDNF prevents neuronal degeneration after axotomy and other forms of neuronal injury [19, 20, 21, 22]. In addition, beneficial effects of BDNF have been reported in animal models of neurodegenerative diseases. Therefore, BDNF is now considered as a potential therapeutic agent for human neurodegenerative disease, for example, motor neuron disease and PD (Figure 1).
Causative and curative roles of BDNF. Schematic view of cognitive dysfunction mediated by binding of pro-BDNF to p75NTR receptor leading to apoptotic cell death. Induction of BDNF gene due to the binding of pro-BDNF to p75NTR + sortilin and mBDNF to TrkB receptors leading to cell survival mediated by NF-κB and CREB, respectively. BDNF, brain-derived neurotrophic factor; mBDNF, mature BDNF; p75NTR, p75 neurotrophin receptor; NRAGE, p75NTR interacting protein; NRIF, neurotrophin receptor interacting factor; TRAF, tumor necrosis factor receptor-associated factor; MKK7, mitogen-activated protein kinase kinase 7; ASK1, apoptotic signal-regulating kinase 1; JNK, c-Jun N-terminal kinase; IRAK, interleukin-1 receptor-associated kinase; IκB, kappa light polypeptide gene enhancer in B-cell inhibitor; NF-κB, nuclear factor kappa-light chain enhancer of B cells; TrkB, tropomyosin receptor kinase B; tPA, tissue plasminogen activator; MAPK, mitogen-activated protein kinase; ERK, extracellular signal-regulated kinase; PI3K, phosphoinositol 3-kinase; AKT, protein kinase B; PLC-γ, phospholipase C gamma; DAG, diacylglycerol; PKC, protein kinase C; IP3, inositol triphosphate; CaM, calmodulin; CaMK, calmodulin-dependent protein kinase; CREB, cyclic adenosine monophosphate response element-binding protein.
The cause of PD is linked with several molecular factors related to the survival and susceptibility of the dopaminergic neurons (DN) of the substantia nigra (SN) [23, 24, 25]. The imbalance in the levels of this neurotrophic factor can affect the motor and cognitive performance in parkinsonian patients. It has been detected that BDNF levels decrease in serum as well as in the SN and caudal-putamen nuclei of patients with PD [26, 27].
Recently, it has been proposed that the detection of a low concentration of BDNF in serum is a biomarker of the early stages of the disease [28, 29]. The low concentration of this neurotrophic factor in serum of PD patients may be due to a low transcription of the BDNF gene. Howells et al. [30] reported that the surviving DN located in the SN of patients with PD contained low levels of BDNF mRNA, suggesting that this condition contribute to the death of DN and to the development of the disease. To counteract the death of DN, Salehi and Mashayekhi [31] proposed that BDNF is produced by glial cells that increase their population as a result of an active response to neurodegeneration, since they reported an increase in BDNF levels in cerebrospinal fluid of patients with PD [31].
Currently, well-known mechanisms of microRNAs (miRNAs) play a crucial role in neurotrophin gene regulation. These miRNAs are short non-coding RNAs of ∼22 nucleotides that are coupled to the RNA-induced silencing complex (RISC) and regulate the degradation of the RNAs [32]. Several miRNAs regulate BDNF expression and could be directly involved in the survival of DN. It has been reported that miR-1 represses the levels of BDNF expression through regulatory sites in the 3′-UTR sequence of the gene [33, 34, 35]. In addition, miR-1 levels have been found to be decreased in patients with PD compared with healthy individuals [36]. The decrease in miR-1 in patients with PD may be due to an activated mechanism to increase the expression of BDNF and promote the survival of the remaining DN in the SN.
In this regard, it has also been reported that BDNF is negatively regulated by the damage induced with neurotoxin in a murine model of Parkinsonism using MPP+. The MPTP neurotoxin is converted to MPP+ by the enzyme monoamine oxidase (MAO-B), expressed by astrocytes. The MPP+ is then internalized into the DN specifically by the dopamine transporter and upon reaching toxic levels in the mitochondria and inhibits the complex I of the electron transport chain [37]. Zhang et al. [38] reported that the treatment with MPP+ led to an increased expression of miR-210-3p and decreased expression of BDNF. To corroborate the results, they performed the inhibition of miR-210-3p and observed that the levels of BDNF increased and the survival of the tyrosine hydroxylase-positive DN of the SN in mice injected with MPTP was also significantly improved. The regulation of BDNF expression has become a key strategy for the rescue of damaged DN in PD.
Another factor that alters the secretion of BDNF is the single nucleotide functional polymorphism Val66Met, whose effect has been widely studied in humans [39, 40, 41]. This polymorphism consists of a substitution of valine amino acid by methionine at position 66 of the precursor protein (pro-BDNF) causing a decrease in secretion induced by depolarization [42]. The distribution of alleles has been reported in several populations, with the Val/Val allele prevailing (from 59 to 72%), followed by Val/Met (from 25 to 38%) and with a lower prevalence of the Met/Met allele (from 2 to 4%) [43, 44, 45]. The effect of polymorphism has been studied with controversial results as some groups argue that there is an advantage of the carriers of the Met/Met allele, by showing a better cognitive performance than the individuals who presented the Val/Met allele [44]; other researchers conclude that the fact of carrying at least one 66Met allele has a high prevalence of having a greater cognitive deterioration when PD is present [43].
One of the main characteristics of PD is the formation of Lewy bodies that are composed mainly of α-synuclein protein [46]. Recently, it was found that this protein interacts with the neurotrophic receptor TrkB, inhibiting its internalization and its correct distribution. This interaction blocks BDNF signaling and results in increased death of DN induced by the MPTP [47]. In addition, α-synuclein has been shown to affect the retrograde axonal transport of BDNF and confirm the inhibition of the signaling pathway in a PD model [48]. The inhibition of this neurotrophic factor makes them susceptible to the DN of the SN and contributes to the symptoms observed in PD.
Currently, PD affects the adult population (˃65 years) and even young people [49, 50]. Although PD is multifactorial, indisputable signs of the disease include the progressive degeneration of the DN of the nigrostriatal pathway due to oxido-redox imbalance, followed by neurodegeneration, neuroinflammation, Lewy bodies’ deposits and the generalized damage of the neural circuits that control movement [24, 51, 52].
The degenerative process develops mainly in the DN. In humans, the early loss of dopaminergic neurons from the SN drastically reduces the striatal dopamine concentration [53, 54]. The origin of the motor and non-motor alterations can be sporadic due to genetic deregulation. Several genetic alterations have been described in α-synuclein, SNCA, PINK 1, DJ-1, LRRK2, ATP13A2, PLA2G6, FBX07, VPS35 and BDNF genes [55, 56]. Independent of the etiologic origin, patients with PD develop motor and even cognitive dysfunctions.
The Parkinson’s motor symptoms are bradykinesia, rigidity, inclined posture and tremor at rest. Neuroimaging studies suggest that the motor signs of the disease appear when 50–70% of the DN damage is present [57]. Tremor at rest is the symptom that is present in more than 70% of the patients with PD; these idiopathic tremors are more noticeable when the patient is not performing a specific movement [58]. Electrophysiological studies suggest that tremor at rest in PD is generated by multiple oscillatory circuits that are operating at the same frequencies (4 ± 6 Hz); this tremor is improved with the administration of levodopa, while orthostatic tremor, in PD, is characterized by rapid and specific tremors that affect the legs and trunk when standing. This tremor presents a frequency of 14 ± 18 Hz, where levodopa has no effect, which indicates that the pathophysiology of orthostatic tremor in PD might be different from the tremor at rest [59].
The bradykinesia or slowness of movement is manifested by the decrease in manual dexterity or the difficulty to get up from where they are sitting. Also during the progress of the disease, patients show postural instability with increased risk of falls as they take much faster and shorter steps, and postural instability has a poor response to dopamine treatments [58]. The symptoms of PD are progressive; however, the rate of progression in motor symptoms is variable according to the period of development of the disease in which they occur [60].
Other motor imbalance is the hypomimia, which is characterized by the decrease in facial expression or in the number of eye blinks, blurred vision, altered look, speech alteration, as well as the presence of dystonia or movement disorders, which causes involuntary contractions of the muscles, stooped posture, difficulty turning, kyphosis or scoliosis, which refer to an abnormal curvature of the spine, walking with the drag of the feet, or “freezing” or inability to move in patients with advanced stage of PD [59].
In functional magnetic resonance imaging studies (fMRI) of akinetic patients, changes have been observed during the performance of a complex sequential motor task, showing a reduced functional magnetic resonance signal in the rostral part of the supplementary motor area and in the right dorsolateral prefrontal cortex. In addition, these patients also showed a significant bilateral increase in the activation of the primary sensorimotor cortex, the premotor cortex lateral, the caudal part of the supplementary motor area, the inferior parietal cortex and the anterior cingulate cortex, and in other cortical motor areas [61]. It has been mentioned that during the earliest pathological stage of PD, neuronal degeneration occurs in motor nuclei of the brainstem, olfactory bulbs and limbic areas; as it proceeds, it continues to the temporal and paralimbic cortices, as well as to the thalamic nuclei, until reaching associative areas such as the prefrontal lobes, and to finally involve the first order and sensory motor areas [62, 63, 64].
However, Agosta et al. [65] found that the progression of the disease in patients with moderate and severe PD shows a small cortical atrophy compared with healthy individuals; this atrophy involves the thalamus and the prefrontal cortex; they also report that the loss of gray matter did not significantly worsen in later stages of the disease, with the thalamus showing this atrophy. They also observed that a microstructural damage of the white matter (WM) occurs with the increase in the severity of the disease, involving the brainstem, cerebellum, thalamocortical, interhemispheric and limbic pathways, as well as the extra motor association tracts. They correlate the damage in WM with the degree of cognitive deficit, considering that the damage in WM probably contributes to the more severe motor and non-motor dysfunctions that occur in patients in later stages.
Parkinson’s disease is associated with multiple cognitive deficits and an increased risk of dementia, especially in its late stage. In addition, alterations in visuospatial, attentional, executive and memory functions may occur [66]. Epidemiological studies show that cognitive impairments are present between 24 and 62% of patients with newly diagnosed PD, and in the long term about 15% of patients remain cognitively intact [67]. The incidence of dementia is approximately 100 per 100,000 patients per year among patients with PD, suggesting that people with PD have a three to six times greater risk of developing dementia than people of the same age without PD [68]. However, the pathophysiological mechanisms involved in these cognitive deficits are not yet clear.
At present, neurotrophic factors have attracted attention from both clinical and experimental levels. BDNF is one of the key molecules in the modulation of cerebral plasticity and can induce long-term potentiation (LTP) through the activation of signal transduction routes; this LTP plays a key role in the neurophysiological basis for learning and memory [69]. In experimental animal models, it has been observed that the inhibition of BDNF signaling in knockout mice can affect spatial learning and memory; on the contrary, in the general population, it has been observed that at higher levels of BDNF in the hypothalamus there is a better cognitive function, including memory [70]. Recently, it has been detected that serum levels of BDNF decrease significantly in those diseases with cognitive deficits, such as Alzheimer’s disease, mild cognitive impairment and Huntington’s disease [27, 71, 72].
At the clinical level, there has been an association between serum BDNF levels and cognitive impairment. For example, one study observed the association between the decreased levels of BDNF present in cerebrospinal fluid, which contributes to early cognitive deterioration in PD, in particular to executive-attentional dysfunction [20]. On the other hand, an increase in BDNF concentrations has been detected in the same sample type of individuals with this pathology with respect to non-diseased controls [31], which could be due to a glial activation to increase the synthesis of this neurotrophin in response to brain damage [19]. Some authors have reported the association between the Val66Met BDNF polymorphism and cognitive dysfunction in patients with PD [43, 44]; subjects with Met BDNF allele show decreased cognitive flexibility when compared to homozygous carriers of the Val BDNF allele [45] (Figure 2).
Val 66 Met/G196A BDNF polymorphism in Parkinson’s disease. Schematic representation showing the structure and location of BDNF gene and the location of single nucleotide polymorphism (SNP) that leads to the disease. BDNF, brain-derived neurotrophic factor.
In basic research, it has been observed that a higher concentration of hippocampal BDNF improves spatial memory in Morris’s water maze [73]. The hippocampus is an important nucleus for learning and memory consolidation processes, and since BDNF plays an important role in the neuroplasticity of the hippocampus, the absence of this neurotrophin might affect the processes of learning and memory in the short and long term. Also, BDNF as well as TrKB has been shown in animal models to participate in the survival of DN in the SN [74], which is one of the main populations affected in PD. Therefore, the deficiency of BDNF, as well as its TrKB receptor, could be related to the loss of DN and the progression of the disease.
In studies of patients with dopaminergic neurodegeneration, a reduction in serum BDNF levels was observed, accompanied by a loss of striatal dopamine transporter (DAT) binding, that is, a positive correlation was found between the striatal DAT junction and BDNF levels [75]. On the other hand, there are several reports showing an increase in serum BDNF levels and also improvement in cognitive performance in PD patients, who underwent cognitive rehabilitation, when compared to a placebo group. These findings suggest that serum BDNF levels may represent a biomarker for the effects of cognitive rehabilitation in PD patients affected with mild cognitive impairment [76].
Aging is another important variable that not only leads to the slow progression of PD but also hampers the medical treatment response [77]. There is aging without PD, but there is no PD without aging [78], showing decreased dopamine levels, increased sensitivity to mitochondrial dysfunction, alterations in calcium channel activity, accumulation of iron and neuromelanin, changes in protein degradation pathways [79], striatal spine retraction [80] and loss of striatal spine density [81]. With advancing age, the loss of DA neurons is fully expressed in PD genetic models in C. elegans [82] and human-induced pluripotent stem cells [83]; thus, aging is the key to the pathogenesis of PD [84]. In PD patients, aging leads to severe gait disturbances including musculoskeletal rigidity, axial impairment and age-related dementia [85].
In the brain, next to nigrostriatal pathway, hippocampus is highly sensitive to aging and BDNF is critically involved in the regulation of age-related hippocampal decline [86]. In normal striatum, BDNF maintains dendritic spine density and synapse function, whereas in aged striatum, impaired BDNF signaling is common, which is further intensified in BDNF Val66Met SNP individuals [87]. With an increase in human age, BDNF mRNA levels remained same but TrkB mRNA levels decreased in hippocampus [88], indicating that BDNF-TrkB system of hippocampus is sensitive to aging [89] and deficiency of BDNF-TrkB signaling leads to the progression of PD [74]. Recent reports in aged brain suggest a diminished capacity of aged brain to transcribe, release and/or respond to BDNF [87]. As a result, treatment with TrkB agonist activates TrkB and downstream signaling cascades in BDNF-independent manner, which is neuroprotective both in vitro and in vivo [90].
At pre-clinical level, alterations in the synthesis and presence of BDNF are related to psychiatric disorders such as anxiety and depression [91, 92]. PD patients with Val66Met BDNF and G/G-BDNF-Val66Met polymorphisms are more predisposed to develop symptoms of anxiety or depression when observed at genetic level [39]. At the protein level observation, pro-BDNF is a facilitator of hippocampal long-term depression (LTD), and Val66Met pro-BDNF impairs memory function but pro-BDNF with Met completely inhibits hippocampal LTD indicating the antagonistic activities of pro-BDNF and BDNF on hippocampal LTD [93]. A post-mortem study on PD patients who received antidepressant drugs reported that the treatment with antidepressants can induce BDNF expression in hippocampus [94]. However, activity-dependent secretion of BDNF and understanding the mechanism of p75NTR-pro-BDNF pathway are crucial to completely understand the hippocampal LTD modulation [93].
In this context, murine models has led to demonstrate the presence of the Val66MetBDNF polymorphism associated with anxiety-like behavior and significant increase of corticosterone, the physiological stress hormone, in serum [95]. Similar to human findings, the decreased production of BDNF in the hippocampus, amygdala and prefrontal cortex [96, 97] can be reversed with antidepressant drugs [91]. Whereas Tuon et al. evaluated the anti-depressant effect of BDNF, in a 6-hydroxydopamine (6-OHDA) murine model, by replacing the pharmacological therapy with physical exercise and observed a decrease of depressive-like behavior, which was associated with the restoration of pro-BDNF, BDNF and TrkB receptor levels both in the hippocampus and the striatum of rats [98].
Despite the importance of BDNF in plasticity and cellular maintenance, the serum levels of this NT have been studied [99]. Existing evidence shows that low concentration of BDNF is a risk factor to generate depression in PD patients [100].
In brain, BDNF not only mediates region-specific effects on synaptic function and neuronal morphology [8] but is also involved in various functions including aging [101], anxiety [102], chronic pain [103], deafness [104], depression [105] and long-term memory storage [9]. BDNF is proven to be the best therapeutic gene for treating metabolic syndrome [106], Friedreich’s ataxia [107], neuropsychiatric or neurocognitive disorders [108], brain ischemia [109], schizophrenia [110], glaucoma [111], epilepsy [112], spinocerebellar ataxia typ. 6 [113], Huntington’s disease [21], multiple sclerosis [114], amyotrophic lateral sclerosis [115], spinal cord injury [116], Alzheimer’s disease [22] and PD [117].
Despite encouraging and numerous researches supporting the potential therapeutic role of BDNF in non-human primate trials, no satisfactory results were found in clinical trials due to the disability to cross blood-brain barrier (BBB) and to reach degenerating neurons as such [118]. Hence, alternative methods like addition of poly ethylene glycol (PEG), either at N-terminal or at C-terminal, and vector-mediated BBB drug delivery were done to improve the BDNF distribution for use in clinical trials [119].
However, very short half-life of BDNF limits the effectiveness as a therapeutic protein, and thus, exogenous delivery methods are necessary to translate BDNF-based therapies to the clinic. In this direction, gene delivery methods through viral vectors have gained lot of attention by researchers in the beginning, but later on, it was proved that the use of viral vectors in the clinic was proven difficult due to the limited biodistribution and host immunogenicity [120]. Later on, non-viral and nanocarrier (liposome and polyplex) mediated gene delivery drew the attention as nanotechnology offers new possibilities for designing vehicles. Along with the nanotechnology, proteomics also integrated leading to the production of fusion protein vectors and mimetics (both protein and non-protein). The outline of the potential therapeutic role of BDNF in treating neurodegenerative disorders, specific focus on PD, by various researches (Table 1) and the patents related to BDNF (Table 2) are tabulated.
Animal model (toxin) | Mode of BDNF supply | Result/outcome |
---|---|---|
Mouse (MPTP) [121, 122, 123] | Intranigral | Increased cell survival |
Non-peptide mimetics of BDNF | ||
Rat (6-OHDA) [117, 124, 125, 126, 127] | Intranigral transplants of human mesenchymal stem cells (hMSC) secreting the BDNF protein | Regulated neurotrophic effect and proved vehicle for the targeted neurotrophic delivery |
Intranigral injections of recombinant human BDNF in healthy rats | Chronic BDNF did not attenuate dopaminergic parameters in either striatum or SN | |
Intra ventricular infusion | Adult brain parenchyma may recruit and/or generate new neurons | |
Intranigral neurotensin (NTS)-polyplex nanocarrier mediated gene delivery | Neurorecovery by neuritogenesis in early stage of PD | |
Intranigral recombinant adeno-associated virus (rAAV) vector-mediated gene delivery | No signs of neuroprotection | |
Rat (MPTP) [128] | Transplanting genetically engineered fibroblasts expressing BDNF protein | Axonal regeneration |
Monkey (MPTP) [129] | Intrathecal infusion | Less neuronal loss and damage was observed in SN |
Rhesus monkey [130, 131] | Stimulation of BDNF secretion by caloric restriction; physical exercise | Increased neuronal survival and locomotor activity in both SN and striatum |
Therapeutic research works using BDNF.
Assignee/s | Inventor (date) | Title |
---|---|---|
Max-Planck Gesellschaft zur Forderung der Wissenschaften, Regeneron Pharmaceuticals Inc. | Yves-Alain Barde (1989) | Brain derived neurotrophic factor |
Synergen Inc. | Frank Collins (1990) | Production of biologically active recombinant members of the NGF/BDNF family of neurotrophic proteins |
Teva Pharmaceutical Industries Ltd. | Liat Hayardeny (2009) | Treatment of BDNF-related disorders using laquinimod |
Center for research and advanced studies of the national polytechnic institute | Daniel Martinez-Fong (2012) | Compositions and methods for Parkinson’s disease treatment by BDNF-flag gene transfer through neurotensin polyplex to nigral dopamine neurons |
Curna Inc., The Scripps Research Institute | Faghini Mohammad Ali and Coito Carlos (2013) | Treatment of brain derived neurotrophic factor related diseases by inhibition of natural antisense transcript to BDNF |
VDF FutureCeuticals | Zbigniew Pietrzkowski (2013) | Compositions and methods of BDNF activation |
Meiji Co., Ltd. | Midori Natsume (2015) | Promoting the production for the composition of the brain-derived neurotrophic factor |
Zhou Yi | Zhou Xinfu (2015) | Application of brain-derived neurotrophic factor precursor protein as target for treating affective disorders |
Patents related to BDNF and its therapeutic role.
The experimental models of Parkinson give evidence of many recovery strategies to BDNF in situ, however till date exist great limitations to use these findings in novel therapies. Some pre-clinical and clinical resources have been patented (Table 2).
The main objectives of experimental and clinical research include better understanding and proper diagnosis, developing new treatments and preventing them to the maximum extent. Currently, there are innumerable experimental pathology studies dedicated to solve the pathophysiology and possible treatment of PD. Based on this, clinical trials offer an excellent opportunity to help doctors and researchers to find better ways in detection, treatment or prevention in a safe way and, therefore, offer hope to people suffering from PD. Current studies include genetics, diagnostic imaging, studies that allow the identification of biomarkers of this disease, pharmacological treatment methods and various proposals for experimental therapies [132, 133]. Development and application of deep brain stimulation through implanting electrodes at specific sites to recover neuronal function is now a treatment option for some people with advanced PD when patients no longer respond to medications [134].
Having PD during aging involves rapid progression of motor impairment, altered mood and cognitive dysfunction. At the cellular level, there is a rapid loss of function and neuronal survival due to the absence of production of neurotrophic factors such as BDNF. In the preclinical phase, some experimental approaches evaluated in animal models have partially prevented the DN degeneration and neuroinflammation. However, these approaches have great challenges; the therapies should be specific to one cell population, guarantee biosafety for human use, low cost and induce a sustained therapeutic effect.
Although BDNF was found to be promising in animal models of PD, no significant results from clinical trials are reported [135], and thus, therapeutic usage of BDNF for PD in humans is not yet reported. However, as BDNF cannot pass through the BBB, intracranial administration is must and this may be overcome by delivering BDNF bound to certain molecular carriers that can cross BBB to avoid intracranial surgery-related complications and long-term effects on behavioral disorders [136]. In this aspect, researchers from University of California have combined BDNF with mesenchymal stem cells (MSC) for treating neurodegenerative diseases, but no published scientific reports exist on preclinical and clinical trials of MSC/BDNF stem cell product [137].
Brain-derived neurotropic factor is relevant to neuronal maintenance and participates in the survival of dopaminergic neurons. The deficit of this neurotrophin is the key for the pathophysiology of PD because it limits the regeneration of motor and cognitive circuits. The absence of BDNF could promote the cognitive dysfunction in vulnerable subjects. The knowledge of the synthesis and delivery routes of this neurotrophin will allow the search for better therapies focused in patients with neurodegenerative diseases.
This work was supported by Consejo Nacional de Ciencia y Tecnologia (Catedra CONACyT # 1840) for DH-B and TC-LL, the Instituto de Neuroetologia from Universidad Veracruzana (DGI-174332015137 & CA-UV025) to MJR-H, the Instituto Mexicano del Seguro Social (FIS/IMSS/PROT/G15/1480) to LMZ-F and PRODEP (UANL-PTC-908) to AV-O. AP-O received fellowship from CONACyT for postgraduate studies in Neuroethology (# 297410).
The authors declare that there are no conflicts of interest.
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